Sen Hu
Software Engineer at Facebook
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSen Hu is a software engineer with a decade of experience building scalable systems for mobility and consumer platforms, currently at Facebook in Sunnyvale. He brings deep expertise in autonomous driving software from his senior roles at DiDi and Baidu USA, contributing to Apollo—one of the leading open-source autonomous driving platforms—where he improved vehicle trajectory control, added reverse gear support, and helped bootstrap routing features. With a strong foundation across mechanical, electrical, and computer engineering and a perfect master's GPA in computer science, he blends cross-disciplinary thinking with practical backend and embedded systems skills. His background includes embedded software at Cummins and production-facing engineering at large-scale consumer and mobility companies, evidencing an ability to move features from research prototypes into production. Colleagues rely on him for thoughtful systems design that balances control, planning, and configuration tooling in complex, safety-critical domains.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BS), Mechanical Engineering, 3.88, Bachelor of Science (BS), Mechanical Engineering, 3.88 at Virginia TechMaster's Degree, Computer Science, 4.00, Master's Degree, Computer Science, 4.00 at Georgia Institute of Technology
English, Chinese, Czech, German
Github Skills (6)
control-systems10
python10
autonomous-driving10
url-routing9
cprogramming-language7
c-language7
Programming languages (2)
Github contributions (5)
ApolloAuto/apollo
Jul 2017 - Sep 2017
An open autonomous driving platform
Role in this project:
Back-end Developer
Back-end DeveloperContributions:114 commits, 15 PRs, 5 pushes in 2 months
Contributions summary:Sen primarily contributed to the `apolloauto/apollo` repository, an autonomous driving platform, by modifying and enhancing existing code related to the platform's core functionality. Their work focused on ensuring vehicle trajectory adherence and developing tools to update configuration files. Further contributions included implementing reverse gear capabilities and adding initial routing features. These modifications suggest a focus on improving the platform's control and planning capabilities.
autonomousmachine-learningautonomyautonomous-drivingapollo
henryhu6/pytorch
Feb 2024 - Feb 2025
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:18 pushes, 6 branches in 11 months
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